Autonomy Architectures for Safe Planning in Unknown Environments Under Budget Constraints
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866914082024587264 |
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| author | Cherenson, Daniel M. Agrawal, Devansh R. Panagou, Dimitra |
| author_facet | Cherenson, Daniel M. Agrawal, Devansh R. Panagou, Dimitra |
| contents | Mission planning can often be formulated as a constrained control problem under multiple path constraints (i.e., safety constraints) and budget constraints (i.e., resource expenditure constraints). In a priori unknown environments, verifying that an offline solution will satisfy the constraints for all time can be difficult, if not impossible. We present ReRoot, a novel sampling-based framework that enforces safety and budget constraints for nonlinear systems in unknown environments. The main idea is that ReRoot grows multiple reverse RRT* trees online, starting from renewal sets, i.e., sets where the budget constraints are renewed. The dynamically feasible backup trajectories guarantee safety and reduce resource expenditure, which provides a principled backup policy when integrated into the gatekeeper safety verification architecture. We demonstrate our approach in simulation with a fixed-wing UAV in a GNSS-denied environment with a budget constraint on localization error that can be renewed at visual landmarks. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2504_03001 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Autonomy Architectures for Safe Planning in Unknown Environments Under Budget Constraints Cherenson, Daniel M. Agrawal, Devansh R. Panagou, Dimitra Robotics Systems and Control Mission planning can often be formulated as a constrained control problem under multiple path constraints (i.e., safety constraints) and budget constraints (i.e., resource expenditure constraints). In a priori unknown environments, verifying that an offline solution will satisfy the constraints for all time can be difficult, if not impossible. We present ReRoot, a novel sampling-based framework that enforces safety and budget constraints for nonlinear systems in unknown environments. The main idea is that ReRoot grows multiple reverse RRT* trees online, starting from renewal sets, i.e., sets where the budget constraints are renewed. The dynamically feasible backup trajectories guarantee safety and reduce resource expenditure, which provides a principled backup policy when integrated into the gatekeeper safety verification architecture. We demonstrate our approach in simulation with a fixed-wing UAV in a GNSS-denied environment with a budget constraint on localization error that can be renewed at visual landmarks. |
| title | Autonomy Architectures for Safe Planning in Unknown Environments Under Budget Constraints |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2504.03001 |